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Design of stand-alone electrification systems using fuzzy mathematical programming approaches

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  • Galleguillos-Pozo, R.
  • Domenech, B.
  • Ferrer-Martí, L.
  • Pastor, R.

Abstract

Currently, around 1.1 billion people lack access to electricity, mainly in developing countries. Solar photovoltaic systems can provide electricity, but the design is complex, having to size and site the equipment. Besides, since forecasting consumption habits for newly electrified populations is complex, the estimation of the electricity needs is uncertain. This work addresses, for the first time, demand uncertainty to assist promoters in designing electricity access projects, simultaneously solving the sizing and siting problems, using fuzzy logic. In particular, a mathematical model is proposed, introducing uncertainty through five modelling approaches with different fuzzy logic assumptions: three based on the literature and two novel ones according to the conflicting problem nature (project cost minimisation vs electricity supply maximisation). The five approaches are compared and the new ones obtain solutions achieving a higher satisfaction regarding the cost and electricity supply. Then, the most efficient approach is applied in two Peruvian communities, comparing the solutions with those obtained without uncertainty. The results of the proposal show a better balance between the project cost and the demand supplied. Hence, the proposal can help promoters in developing countries to better design electricity access projects where the demand estimation is complex.

Suggested Citation

  • Galleguillos-Pozo, R. & Domenech, B. & Ferrer-Martí, L. & Pastor, R., 2021. "Design of stand-alone electrification systems using fuzzy mathematical programming approaches," Energy, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:energy:v:228:y:2021:i:c:s0360544221008884
    DOI: 10.1016/j.energy.2021.120639
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    2. Xie, Rui & Wei, Wei & Li, Mingxuan & Dong, ZhaoYang & Mei, Shengwei, 2023. "Sizing capacities of renewable generation, transmission, and energy storage for low-carbon power systems: A distributionally robust optimization approach," Energy, Elsevier, vol. 263(PA).
    3. Akbas, Beste & Kocaman, Ayse Selin & Nock, Destenie & Trotter, Philipp A., 2022. "Rural electrification: An overview of optimization methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    4. Bruno Domenech & Laia Ferrer-Martí & Facundo García & Georgina Hidalgo & Rafael Pastor & Antonin Ponsich, 2022. "Optimizing PV Microgrid Isolated Electrification Projects—A Case Study in Ecuador," Mathematics, MDPI, vol. 10(8), pages 1-24, April.

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